Zahoor Ahmad Najar’s research while affiliated with Central University of Kashmir and other places

The Internet of Things (IoT) and Wireless Sensor Networks (WSNs) have rapidly spread in recent decades, leading to remarkable innovation and integrated possibilities. The switch from IPv4 to IPv6, made possible by advancements in networking technology and the use of nanodevices, has further improved connectivity. This move allows for connecting a wider range of devices to servers. Nevertheless, the increasing interconnectivity has brought about difficulties in efficiently overseeing and analysing the enormous amount of data produced throughout all levels of the IoT. The requirement of comprehensive security management is particularly concerning for IoT devices due to their large quantity and small size. Within the layered architecture of IoT, the network layer assumes pivotal importance in ensuring security, bearing responsibility for storing routing information and executing corresponding decisions. The Black Hole attack is a frequently encountered and significant concern among the security attacks addressed. This paper thoroughly examines the consequences of the Black Hole attack on IoT networks, carefully analyzing its impact. Furthermore, it presents a novel mitigation algorithm designed to counter such threats efficiently. The research employs NS2 and Simulink to run extensive simulations, enabling the evaluation of network throughput and Packet Delivery Ratio (PDR). Applying the proposed mitigation strategy to a network affected by the Black Hole attack results in a significant improvement in throughput, which closely resembles that of an unaffected network. The observed Packet Delivery Ratio (PDR) is measured at 98.21%. This highlights the algorithm’s effectiveness in mitigating the detrimental effects of the Black Hole attack on IoT networks.

Cloud is used to store and process data at a very high rate. Moreover, nearly everyone in this world is using the cloud. However, the problem arises that the data centers are not positioned well. The data reach the cloud by passing through the various links, due to which more delays occur. So this world is now moving into fog. Fog computing provides us the capability to process data nearer to the IoT devices. During the past decade, IoT devices have been growing rapidly, resulting in the production of a tremendous amount of data every day. For the processing of this ever-growing data, efficient algorithms are required to reduce the load on the cloud and give the results in a faster and more precise manner. The processing should be done on the fog node to handle this issue. In this paper, the authors study load balancing on fog nodes with a novel technique so that they distribute the load among different fog nodes so that none of the fog nodes remains idle while other takes time for processing the data.